Non-parametric tests in detecting glaucoma progression.

Rom J Ophthalmol

Surgery Department, Ophthalmology Unit, "Gr. T. Popa" University of Medicine and Pharmacy, Iași, Romania.

Published: July 2018

Automated perimetry still represents the gold standard in long term glaucoma monitoring. On a daily practice basis, glaucoma progression analysis could be difficult due to the long time needed to detect, confirm, and quantify the progression rate. Moreover, "trend" and "event" analysis require a good theoretical basis to perform and interpret. was to present an alternative method to conventional Glaucoma Progression Analysis (Humphrey Visual Field Analyzer, Carl Zeiss® Inc.) applied for the early detection of glaucoma progression. Such an "event" analysis orients the clinician in a fast manner on the progression profile in glaucoma patients and might adapt the follow up visits accordingly. 41 eyes from 41 patients with open angle glaucoma were studied in a longitudinal manner, over a 24 months' time interval from diagnosis. in the GPA analysis, a positive "event" (progression) was detected in 11/ 41 eyes (26.82%). Non-parametric analysis confirmed progression in all GPA cases, and additionally found 8 more eyes with positive progression (46.34% studied eyes). Mc Nemar concordance analysis between tests was good and relevant (kappa index k=0.596, p=0.000), with positive correlation (r=0.652, p=0.008). In , NPA tends to overestimate the number of progression cases in a cohort, but it can easily orient the clinician on the profile of the followed patients. In the first years, the GPA analysis can be highly inaccurate, but there is a great need to detect which patients are at significant risk for vision loss (fast progressors). Yet, combining the two methods of detection of glaucoma progression, the practitioners might direct their selected interest and attention towards observing a larger than expected number of patients who are at risk for vision loss over time due to glaucoma, but not necessarily in a fast manner.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5710041PMC
http://dx.doi.org/10.22336/rjo.2017.39DOI Listing

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